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Gait Kinematic Parameters in Parkinson’s Disease: A Systematic Review

BACKGROUND: Gait impairments are common and highly disabling for Parkinson’s disease (PD) patients. With the development of technology-based tools, it is now possible to measure the spatiotemporal parameters of gait with a reduced margin of error, thereby enabling a more accurate characterization of...

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Detalles Bibliográficos
Autores principales: Bouça-Machado, Raquel, Jalles, Constança, Guerreiro, Daniela, Pona-Ferreira, Filipa, Branco, Diogo, Guerreiro, Tiago, Matias, Ricardo, Ferreira, Joaquim J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: IOS Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7458503/
https://www.ncbi.nlm.nih.gov/pubmed/32417796
http://dx.doi.org/10.3233/JPD-201969
Descripción
Sumario:BACKGROUND: Gait impairments are common and highly disabling for Parkinson’s disease (PD) patients. With the development of technology-based tools, it is now possible to measure the spatiotemporal parameters of gait with a reduced margin of error, thereby enabling a more accurate characterization of impairment. OBJECTIVE: To summarize and critically appraise the characteristics of technology-based gait analysis in PD and to provide mean and standard deviation values for spatiotemporal gait parameters. METHODS: A systematic review was conducted using the databases CENTRAL, MEDLINE, Embase, and PEDro from their inception to September 2019 to identify all observational and experimental studies conducted in PD or atypical parkinsonism that included a technology-based gait assessment. Two reviewers independently screened citations and extracted data. RESULTS: We included 95 studies, 82.1% (n = 78) reporting a laboratory gait assessment and 61.1% (n = 58 studies) using a wearable sensor. The most frequently reported parameters were gait velocity, stride and step length, and cadence. A statistically significant difference was found when comparing the mean values of each of these parameters in PD patients versus healthy controls. No statistically significant differences were found in the mean value of the parameters when comparing wearable versus non-wearable sensors, different types of wearable sensors, and different sensor locations. CONCLUSION: Our results provide useful information for performing objective technology-based gait assessment in PD, as well as mean values to better interpret the results. Further studies should explore the clinical meaningfulness of each parameter and how they behave in a free-living context and throughout disease progression.